Content development and distribution using cognitive sciences database

ABSTRACT

Computer implemented methods and systems facilitate development and distribution of content for presentation on a display or a multiplicity of networked displays, the content including content elements. The content elements may include graphics, text, video clips, still images, audio clips or web pages. The development of the content is facilitated using a database comprising design rules based on principles of cognitive and vision sciences. The database may include design rules based on visual attention, memory, and/or text recognition, for example.

FIELD OF THE INVENTION

The present invention relates to methods and systems for developingcontent for presentation on a display or a multiplicity of networkeddisplays.

BACKGROUND

Designers of content often employ computer application programs that arecapable of importing and arranging various types of content.Advertisements, for example, may be developed that incorporate text,graphics, video, and audio elements, among others. In general, theeffectiveness of advertising content is a function of a designer'sexperience, rather than the sophistication of the computer applicationprogram used to generate the advertising content.

A successful content designer generally improves his or her skills in atrial and error fashion or by relying on tried-and-true approaches.Imparting an accomplished designer's skills to a less experienceddesigner is often difficult if not impossible, as such skills tend to behighly stylistic and personal to the particular designer. Because thecompetency of designers varies significantly, so does the quality andeffectiveness of the content that they produce. Conventional computerapplication programs for generating content generally do not provide thedesigner with tools that allow the designer to exceed his or her ownskills for developing effective content.

SUMMARY OF THE INVENTION

The present invention is directed to systems and methods for developingand distributing content through use of computer assistance. Embodimentsof the present invention are directed to a computer-assisted method fordeveloping content for presentation on a display, the content comprisingcontent elements. The content elements may include graphics, text, videoclips, still images, audio clips or web pages. The method furtherinvolves facilitating, by way of computer assistance, the development ofthe content using a database comprising design rules or models based onprinciples of cognitive and vision sciences. The database may includedesign rules or models based on visual attention, memory, and/or textreadability, for example.

Facilitating the development of the content may involve developing thecontent in compliance with design rules or models, and may involvealerting a user in response to violation of one or more of the designrules or models. Facilitating content development may involve generatinguser perceivable recommendations for developing the content, where therecommendations are consistent with design rules or models. Facilitatingcontent development may involve automatically adjusting the content viacomputer-assistance in response to violation of one or more of thedesign rules or models.

Facilitating the development of the content may involve facilitatingselection and/or layout of the content elements or selection of one ormore attributes of the content elements in compliance with the designrules or models. The attributes of the content elements may include oneor more of color, brightness, size, font, orientation, movement,presentation duration or flash rate, display location, and number ofcontent elements concurrently presented on the display, among others.

Facilitating the development of the content may involve facilitatingselection of content element attributes based on one or more attributesof the display. The display attributes may include one or more ofdisplay type, display size, display shape, average viewing distance fromthe display, average speed of viewer movement relative to the display,viewer dwelling time, ambient lighting at a location of the display, andtime of day of content presentation on the display, among others.

According to some implementations, user input data is received regardingeach content element, the user input data including informationconcerning one or both of content goal and intended message. In suchimplementations, facilitating the development of the content may involvefacilitating development of the content using the design rules or modelsand the user input data.

The content may be developed for presentation on a multiplicity ofnetworked displays, and may involve selection of content elementattributes based on one or more attributes of each of the displays.According to some implementations, user input data regarding eachcontent element is received, the information comprising one or both ofcontent goal and intended message. Attributes of the networked displaysare identified that have implications for content development. Contentdevelopment is facilitated using the design rules or models, user inputdata, and display attributes.

Methods of the present invention may further involve facilitating, byway of computer assistance, modification of the developed content incompliance with the design rules or models. The developed content may bemodified in response to a change in one or more attributes of one ormore displays of a display network, such as display type, display size,display shape, expected viewing distance from the display, ambientlighting at a location of the display, and time of day of contentpresentation on the display, for example.

According to other embodiments, systems of the present invention mayinclude a database comprising design rules or models based on principlesof cognitive and vision sciences, a user interface comprising a display,and a processor coupled to the database and user interface. Theprocessor is configured to facilitate development of content forpresentation on the display in compliance with the design rules ormodels. The processor may be configured to implement one or more of themethods described hereinabove.

Embodiments of the present invention are further directed to systems andmethods that provide for computer-assisted analysis of content by one ormore cognitive and vision sciences (CVS) models. Content is provided ordeveloped by a content designer. The content is input to a computer thatimplements one or more CVS models, such as a computational model ofvisual attention, a text readability model or a model of human memory.The CVS model or models perform an analysis on the content and producean output based on the analysis results. Information representative ofenvironmental conditions at the presentation locations and/or goals forthe content may be inputs to the model(s). For example, the type ofdisplays and average distance between displays and viewers may beenvironmental condition information that is input to the model(s).

Goal information that may be input to the model(s) may include goalsthat are associated with each of the various models, such ascomputational model of visual attention, a text readability model or amodel of human memory. Typical goal information may include specificelements of the content to be perceived by viewers and the desired orderin which such specific elements are perceived. Other goal informationmay include improving or optimizing text readability based on text sizeand/or scrolling text rate relative to viewer location and/or speed atwhich viewers pass by a given display. Additional goal information mayinclude maximizing memory retention and recall of content by viewers,such as by conforming to memory capacity and duration rules of a givenmodel.

In some implementations, the output represents recommendations forchanging the content in conformance with a given model's rules or goals.The recommendations may take several forms, such as a narrative form orimages. For example, a menu of possible attributes of the content thatmay be changed can be presented to the user. The menu of attributes mayinclude a range of attribute values that may be changed by the user, yetstill conform with a given model's rules or goals. In otherimplementations, the output represents a modified form of the originalcontent produced automatically by the computer implemented CVS model ormodels. A number of variations of modified content may be automaticallyproduced, each of which satisfies the rules or goals of the model ormodels. The user may then select a desired version of the modifiedcontent for presentation. Alternatively, the computer may select one ormore of the versions for presentation. In other implementations, thevarious versions of modified content may be subject to a designedexperimental process that improves or optimizes content presentationeffectiveness for a number of networked displays, preferably on adisplay-by-display basis.

According to other embodiments, content may be developed and distributedin conformance with cognitive and vision sciences rules or models. Atrue experiment may be performed to improve or optimize presentationeffectiveness of the content. A quasi-experiment or correlationalexperiment may also be performed to improve or optimize presentationeffectiveness of the content. Conducting the true experiment may includeidentifying dependent variables, such as a goal of increasing sales of aparticular product. Independent variables may be identified, such asparameters associated with one or more CVS models (e.g., textreadability, visual attention and/or memory parameters). Content may bemodified in view of the results from the true experiment orquasi-/correlational experiment. For example, content may be modified ona display-by-display basis, based on improved or optimized parametersfor each display. The modified content may be presented on each of thedisplays. Additional true or quasi-/correlational experimentation may beconducted to further improve or optimize content presentation,particularly under changing environmental conditions or a change in thegoals or intended message of the content.

The above summary of the present invention is not intended to describeeach embodiment or every implementation of the present invention.Advantages and attainments, together with a more complete understandingof the invention, will become apparent and appreciated by referring tothe following detailed description and claims taken in conjunction withthe accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates various processes associated with the development ofcontent in accordance with embodiments of the present invention;

FIG. 2 illustrates various processes associated with the development ofcontent in accordance with other embodiments of the present invention;

FIG. 3 illustrates various processes associated with the development ofcontent in accordance with further embodiments of the present invention;

FIG. 4A depicts an initial attempt by a designer to create apresentation for display that includes a number of different contentelements;

FIG. 4B illustrates how the developed content shown in FIG. 4A is moreappropriately arranged in a manner consistent with design rules ormodels that are based on principles of cognitive and vision sciences inaccordance with embodiments of the present invention;

FIG. 5 is a block diagram of a system for implementing computer-assisteddevelopment of content using principles of cognitive and vision sciencesin accordance with embodiments of the present invention;

FIG. 6 is a block diagram of a system for implementing computer-assisteddevelopment and/or distribution of content in a manner consistent withprinciples of cognitive and vision sciences in accordance withembodiments of the present invention;

FIG. 7 is a block diagram of a digital signage system that incorporatesthe capability for developing and distributing content in accordancewith embodiments of the invention;

FIG. 8 illustrates the process flow of creating and deploying contentusing the components and functionality of the digital signage systemshown in FIG. 7;

FIG. 9 is a flowchart illustrating an exemplary implementation of adigital signage system in accordance with embodiments of the presentinvention;

FIG. 10 is a block diagram of a system for developing and/ordistributing content using cognitive/vision science driven software inaccordance with embodiments of the present invention;

FIG. 11 is a flowchart illustrating various processes associated withcontent development and modification using one or more cognitive/visionsciences models in accordance with the present invention; and

FIG. 12 is a flowchart illustrating various processes associated withcontent development and modification of same using one or morecognitive/vision sciences models and results from true experimentationpreferably implemented by a digital signage system in accordance withthe present invention.

While the invention is amenable to various modifications and alternativeforms, specifics thereof have been shown by way of example in thedrawings and will be described in detail. It is to be understood,however, that the intention is not to limit the invention to theparticular embodiments described. On the contrary, the intention is tocover all modifications, equivalents, and alternatives falling withinthe scope of the invention as defined by the appended claims.

DETAILED DESCRIPTION OF VARIOUS EMBODIMENTS

In the following description of the illustrated embodiments, referenceis made to the accompanying drawings that form a part hereof, and inwhich is shown by way of illustration, various embodiments in which theinvention may be practiced. It is to be understood that the embodimentsmay be utilized and structural changes may be made without departingfrom the scope of the present invention.

The present invention is directed to methods and systems for creatingcontent for presentation on a display or a multiplicity of networkeddisplays, and facilitating, by way of computer assistance, contentcreation in a manner consistent with principles based on human cognitivescience and vision science. Methods and systems of the present inventionare also directed to distributing and adjusting content for presentationon a display or a multiplicity of networked displays in a mannerconsistent with principles based on human cognitive science and visionscience. Developing and adjusting content may also involve performingtrue experiments or quasi-/correlational experiments to improve oroptimize content presentation effectiveness. Creating, distributing, andadjusting content in accordance with the present inventionadvantageously enhances the effectiveness of content presentation asperceived by a recipient, such as potential purchaser of goods orservices.

Content creation is preferably conducted in a manner consistent withprinciples based on one or more of how human perceptual systems processinformation, mechanisms that underlie attention, how the human brainstores and represents information in memory, and the cognitive basis oflanguage and problem solving, for example. A knowledge base that storescognitive and vision science information is preferably utilized duringthe content design, distribution, and/or adjustment processes in orderto provide content that is easily processed by human perceptual systems,easily comprehended, and easily stored in memory. The knowledge base mayinclude design rules and templates that may be implemented by a computerto develop and modify content in conformance with principles ofcognitive and vision sciences. The knowledge base may also includecomputer implementable models of principles of cognitive and visionsciences, such as models of visual attention, text readability, andmemory principles. Computer assisted methods and systems of the presentinvention allow content designers, who typically do not have thetraining required to apply principles from cognitive science and visionscience, to increase the effectiveness of content design anddistribution.

In some embodiments, computer assisted methods and systems of thepresent invention may be implemented to operate in a semi-automaticmode, wherein a user is led by the computer through one or moreinteractive sessions to design, develop, distribute, and/or adjustcontent. In other embodiments, computer assisted methods and systems ofthe present invention may be implemented in a more fully automaticmanner, with minimal or no user input or interaction. In a fullyautomatic mode, for example, a computer-based system may create apresentation based on user selected pieces of content in a mannerconsistent with design rules or models stored in a cognitive sciencesdatabase. User selected pieces of content may be arranged, sized, and/ororiented on a user's display based on the design rules or models, andfurther in view of the goal and/or intended message of the contentpieces as indicated by the user. A fully automated implementation mayinvolve the computer-based system adjusting content elements of a givenpresentation based on one or more of the design rules or models, goal ofthe content pieces, and intended message of the contend pieces. Theseare but a few illustrative examples of possible levels of automaticitythat can be achieved in accordance with the present invention, and arenot to be regarded as exhaustive or limiting.

Aspects of the present invention will generally be discussed herein inthe context of a digital signage system (DSS) or network. A DSS ascontemplated in the particular embodiments described herein includes aseries of interconnected (e.g., networked) display screens that aresimilar to traditional signs, but that can be controlled from a remotelocation to deliver dynamically changing content. Such displays ordigital signs may be configured such that people can directly interactwith signage content via touch screens or human interface devices (e.g.,keyboard or mouse). It is to be understood that principles of thepresent invention may be applied in a wide variety of applications, andare not limited to those involving a DSS. Moreover, it is to beunderstood that implementations of the present invention may varysubstantially in terms of complexity, in that some implementation mayutilize relatively simple principles of cognitive science and/or visionscience (e.g., human visual perception), while others may be ofsubstantial complexity, drawing from multiple disciplines of thecognitive and vision sciences (e.g., human visual attention, memory, andtext readability).

Display technology is becoming increasingly diverse such that there aresignificant differences in the types of displays that can be used topresent content via a DSS. For example, the size, shape, brightness, andviewing conditions will, in general, vary greatly across a DSS. Forexample, some displays may be small, flexible and non-rectilinear,whereas others may be standard large-format LCD and plasma displays.This variation in display types and viewing conditions means that anysingle version of a piece of content will not be optimal for all thedisplays across a DSS.

In order to overcome this problem using a conventional approach, itwould be necessary to generate unique versions of each piece of contentfor each unique display type and viewing environment, and to selectivelydistribute these unique versions of content to their correspondingdisplays in the network. However, it is not realistic to expect contentdesigners to have such detailed knowledge of the display types andviewing conditions across a large network of displays. Furthermore, evenif content designers had such detailed knowledge, it would beprohibitively time-consuming to manually create unique versions ofcontent for each display and to manually schedule the content to play oneach corresponding display at the appropriate time. Methods and systemsof the present invention advantageously allow content designers withoutadvanced training in the visual and cognitive sciences to applyprinciples from these disciplines during the content creation processand during content adjustment, such as during content distribution to anetwork of disparate displays, in order to improve contenteffectiveness.

According to embodiments of the present invention, the user may beprompted during the content creation process to input one or both of thegoal and intended message for each piece of content to be presented.According to various embodiments, the system may assist the user inidentifying key attributes of the DSS that have implications for contentdesign. The system may further guide the user through the process ofapplying the cognitive and vision sciences to design content based onthe goals and key DSS attributes. For example, the system may help userschoose templates (e.g., best layout) and elements (e.g., whetherelements should be graphical, text, involve movement, color, size, etc.)to display on the DSS displays.

According to other embodiments, systems and methods of the presentinvention may implement software that automatically generates newtemplates and applies transformations to existing content elements. Newtemplates and content elements may be generated for various reasons,such as to improve the content effectiveness. Tools are preferably madeavailable to the user that facilitate generation of unique versions ofpieces of content for each display of the DSS. For example, softwaretools may be implemented that elicit input from a user and/or othersoftware components regarding DSS attributes and other factors thatunderlie content effectiveness, and apply information from the cognitiveand visions sciences (e.g., design rules or models accessed from adatabase) to extrapolate, fill in, and otherwise explore the informationspace for the particular pieces of content the system aims to improve oroptimize. Systems and methods of the present invention provide afacility to generate completely new content that is not simply areconfiguration of deployed templates or elements associated withdeployed versions of content. That is, the systems and methods of thepresent invention need not rely solely on the hybridization/blending ofdeployed templates and elements that data suggest are effective,although such systems and methods are capable of hybridization/blending.

Turning now to FIG. 1, there is illustrated various processes associatedwith the development of content in accordance with embodiments of thepresent invention. The term content is a broad term that refers to awide variety of informational content, including graphics, text, videoclips, still images, audio clips, web pages, and/or any combination ofvideo and/or audio content, for example. A piece of content refers to aspecific set and configuration of images, videos, text elements, etc.,that is meant to stand on its own to communicate a specific message orset of messages (e.g., a television commercial). The term contentelement refers to individual images, videos, text strings, etc., thatcan be combined to make specific pieces of content.

Each piece of content can have many versions. For example, two versionsof the same piece of content could differ in that one version uses textto represent a concept whereas another version of that same piece ofcontent might use an icon to represent the same concept. There can alsobe many versions of each content element. For example, one version of atext string could have 12-point font whereas the same text string couldhave 24-point font.

According to the embodiment of FIG. 1, content is developed 10 forpresentation on a display. The development of the content, whichincludes content elements, is facilitated 12, by way of computerassistance. Specifically, design rules or models stored in a databaseare applied to 14 to facilitate computer-assisted development of thecontent. The design rules or models are preferably rules or guidelinesthat are based on principles of cognitive and vision sciences. Thedesign rules/models allow a designer who has limited or no knowledge ofprinciples of cognitive and vision sciences to create effective contentthat is consistent with such principles. The design rules/models storedin the database may be used to facilitate 16 computer-assistedadjustment of the content. The processes of generating content andrevising content in a manner consistent with principles of cognitive andvision sciences are advantageously facilitated by computer assistance toenhance content effectiveness.

FIG. 2 illustrates various processes associated with the development ofcontent in accordance with other embodiments of the present invention.According to the embodiment of FIG. 2, content is developed or adjusted20 for presentation on a display. Design rules or models stored in adatabase are accessed 22 during content development or adjustment. Thedesign rules are rules or guidelines that are based on principles ofcognitive and vision sciences, as previously discussed. The modelsstored in the database are typically based on a combination of rulesthat are associated with a multiplicity of cognitive and vision sciencesprinciples. A computational model of visual attention, for example,represents one such model that encompasses several principles ofcognitive and vision sciences. One particular computation model ofvisual attention may be referred to as a saliency mapping model as isknown in the art. Useful examples of saliency mapping models aredisclosed in U.S. Patent Publication No. 2006/0215922 and in U.S. Pat.No. 7,130,461, each of which is incorporated herein by reference. It isunderstood that a wide range of cognitive and vision science models maybe used in the context of the present invention, and are not limited tomodels of human visual attention as specifically discussed above. Suchother models may include those that encompass human memory principles,for example.

A computer system, which accesses the database that stores the designrules or models, determines 24 if development or adjustment of thecontent is consistent with the design rules/models. Various operationsmay be performed in response to determining that the design rules havebeen violated. For example, a user-perceivable recommendation may begenerated 26 to suggest changes the user can make during contentdevelopment or adjustment to satisfy to the design rules or models. Auser-perceivable alert may be generated 27 that indicates non-compliancewith the design rules or models. Automatic adjustment to the developedcontent may be performed 28 to ensure that the content is consistentwith the design rules or models. FIG. 2 illustrates several of manyother possible events that can be triggered during development oradjustment of content if an inconsistency with the design rules/modelshas been detected. Compliance with the design rules/models can be mademandatory or permissive depending on the application and sophisticationof the user.

FIG. 3 illustrates various processes associated with the development ofcontent in accordance with further embodiments of the present invention.According to the embodiment of FIG. 3, content is developed 30 forpresentation on a multiplicity of displays, such as a network of DSSdisplays. The multiplicity of displays are preferably those associatedwith a DSS, but may be displays associated with any network of displays,such as home computer displays coupled to the internet Design rules ormodels stored in a database are applied 32 during content development,the design rules/models based on principles of cognitive and visionsciences, as previously discussed.

Attributes of each display of the display network are determined 34.Such attributes typically include display type, size, shape,environment, ambient lighting, viewing distance, viewer passing speed,among others. These attributes are preferably determined in an automatedmanner, such as by reading attribute data stored in the display (e.g.,determined and stored during display installation) or from a databasethat contains attribute information for each display. These attributesmay also be determined using one or more sensors located at the viewinglocations. A video camera, for example, may be installed at viewinglocations to facilitate detection of changing environmental conditions,such as day/night changes, density of viewers, and distance between theviewers and the display. Proximity sensors, such as infrared (IR)sensors, may be used at viewer locations to determine the average numberof viewers per unit time and/or average distance between the viewers andthe display.

According to one approach, the content is adjusted 36 to accommodate theattributes of the networked displays in conformance with the designrules/models. For example, the attributes of a 8″ display differsignificantly from those of a large panel display (e.g., 50″ LCDdisplay). The content of a given presentation is preferably adjusted sothat the content elements are presented 38 on each of the disparatedisplays in conformance with the design rules/models.

According to a further approach, as is also shown in FIG. 3, user inputdata is received 35 regarding elements of the content. The user inputdata preferably includes the goal and/or the intended message of eachcontent element. The content is adjusted 37 to accommodate theattributes of the networked displays and the user input data in a mannerconsistent with the design rules/models. The adjusted content ispresented 38 in an appropriate manner on each of the networked displays38.

FIGS. 4A and 4B illustrate how content development for presentation on adisplay 40 may be conducted in a manner consistent with design rulesdeveloped from principles of cognitive and vision sciences. FIG. 4Adepicts an initial attempt by the designer to create a presentation fordisplay that includes a number of different content elements. In thisillustrative example, the designer has selected the following contentelements for presentation on display 40: a text crawl 44, a videoadvertisement 42, a store logo 46, and a weather/news panel 48. Assumingthat the designer is not well acquainted with principles of cognitiveand vision sciences, the layout of these content elements 42, 44, 46,and 48 as shown in FIG. 4A represents what the designer believes to bean effective piece of content.

FIG. 4B illustrates how the developed content shown in FIG. 4A is moreappropriately arranged in a manner consistent with design rules ormodels developed from principles of cognitive and vision sciences. Thelocations and size of the content elements 42, 44, 46, and 48 shown inFIG. 4B have been changed in accordance with design rules/modelsdeveloped from principles of cognitive and vision sciences. Aspects ofthe content elements other than, or in addition to, location and sizerelative to the display 40 may be modified as well, such as font oftext, text orientation, foreground and background colors, colorintensity, proportion of the content elements relative to one another,relative brightness, among others. Adjustment of the content elementsmay be implemented in a semi-automatic or fully automatic manner viacomputer assistance.

FIG. 5 is a block diagram of a system for implementing computer-assisteddevelopment of content using principles of cognitive and vision sciencesin accordance with embodiments of the present invention. The systemshown in FIG. 5 includes a processor 52 coupled to a user interface 54and a display 56. The user interface 54 preferably includes one or moreuser input devices, such as a keyboard, mouse, voice recognitionfacility, and the like. A presentation 58 of content developed inaccordance with the present invention is typically presented on thedisplay 56. Content of the presentation 58 is preferably created andrevised in accordance with design rules or models stored in a cognitivesciences database 50. Various templates (e.g., layouts) that areconsistent with the design rules/models may also be stored in thecognitive sciences database 50. It is understood that the cognitivesciences database 50 typically stores information, such as design rules,templates, and models, that is associated with both cognitive scienceand vision science, and that the use of the term cognitive sciencesdatabase is not exclusive to cognitive science only.

FIG. 6 is a block diagram of a system for implementing computer-assisteddevelopment and/or distribution of content in a manner consistent withprinciples of cognitive and vision sciences in accordance withembodiments of the present invention. The system shown in FIG. 6includes a processor 62 coupled to a user interface 64, a display 66, acognitive sciences database 50, and a network interface 70. The networkinterface 70 facilitates communication between the processor 62 and amultiplicity of displays 80A-80N of a DSS. The processor 62 appliesdesign rules accessed from the cognitive sciences database 50 to formatcontent in a manner tailored for each of the displays 80A-80N, at leastsome of which have differing attributes. The effectiveness of thepresentations 82A-82N distributed to the various displays 80A-80N isenhanced by adjustments made to the content by application of the designrules, models, and templates stored in the cognitive sciences database50, in view of attributes of the DSS. The effectiveness of thepresentations 82A-82N distributed to the various displays 80A-80N may befurther enhanced by modification of the content elements in view ofuser-indicated goals and intended message.

FIG. 7 is a block diagram of a DSS that incorporates the capability fordeveloping and distributing content in accordance with embodiments ofthe invention. The block, diagram of FIG. 7 illustrates oneconfiguration of a DSS divided into functional blocks. Those skilled inthe art will appreciate that the DSS may be alternatively illustratedusing different function blocks and that various components of the DSSmay be implemented as hardware, software, firmware, or any combinationof hardware, software and firmware.

The DSS illustrated in FIG. 7 is a computerized system configured topresent informational content via audio, visual, and/or other mediaformats. The DSS may include functionality to automatically orsemi-automatically generate playlists, which provide a list of theinformation content to be presented, and schedules, which define anorder for the presentation of the content. In a semi-automatic mode, auser may access a DSS control processor 105 via an interactive userinterface 110. Assisted by the DSS control processor 105, the user maydevelop content by identifying content elements to be presented,preferably in accordance with design rules stored in a cognitivesciences database 130. The DSS control processor 105 may then be used togenerate playlists and schedules that control the timing and order ofpresentations on one or more DSS players 115. Each player 115 presentscontent to recipients according to a playlist and schedule developed forthe player 115. As discussed previously, the informational content maycomprise graphics, text, video clips, still images, audio clips, webpages, and/or any combination of video and/or audio content, forexample.

In some implementations, after a playlist and schedule are developed,the DSS control processor 105 determines the content required for theplaylist, downloads the content from a content server, and transfers thecontent along with the playlist and schedule to a player controller 120that distributes content to the players 115. Although FIG. 7 shows onlyone player controller 120, multiple player controllers may be coupled toa single DSS control processor 105. Each player controller 120 maycontrol a single player 115 or multiple players 115. The content and/orthe playlists and schedules may be transferred from the DSS controlprocessor 105 to the one or more player controllers 120 in a compressedformat with appropriate addressing providing information identifying theplayer 115 for which the content/playlist/schedule is intended. In someapplications, the players 115 may be distributed in stores and thecontent presented on the players 115 may be advertisements.

In other implementations, the DSS control processor 105 may transferonly the playlists and schedules to the player controller 120. If thecontent is not resident on the player controller 120, the playercontroller 120 may access content storage 125 to acquire the content tobe presented. In some scenarios, one or more of the various componentsof the DSS system, including the content storage 125, may be accessiblevia a network connection, such as an intranet or Internet connection.The player controller 120 may assemble the desired content, or otherwisefacilitate display of the desired content on the players according tothe playlist and schedule. The playlists, schedules, and/or contentpresented on the players 115 can be modified periodically or as desiredby the user through the player controller 120, or through the DSScontrol processor 105, for example. Such modifications can be made inaccordance with design rules, models or templates stored in thecognitive sciences database 130.

In some implementations, the DSS control processor 105 facilitates thedevelopment and/or formatting of a program of content to be played on aplayer. For example, the DSS control processor 105 may facilitateformatting of an audiovisual program through the use of a template. Thetemplate includes formatting constraints and/or rules that are appliedin the development of an audiovisual program to be presented. Forexample, the template may include rules associated with the portions ofthe screen used for certain types of content, what type of content canbe played in each segment, and in what sequence, font size, orientation,and/or other constraints or rules applicable to the display of theprogram. A separate set of rules and/or constraints may be desirable foreach display configuration. These rules, templates, and constraints(e.g., design rules/models/templates) are preferably stored and accessedfrom the cognitive sciences database 130. In some embodiments,formatting a program for different displays may be performedautomatically by the DSS control processor 105 in accordance with thedesign rules. models, and templates.

The information stored in the cognitive sciences database 130 may beused automatically or semi-automatically to control, adjust, and/ormonitor one or more processes of the DSS including creation oftemplates, content design, selection of content, distribution ofcontent, assembly of programs, and/or formatting of programs fordisplay. The cognitive sciences database 130 used in conjunction withthe programming of the DSS yields advertisements or other digitalsignage programs that are enhanced by the teachings of cognitivescience, while relieving the system user from needing specific trainingin the field.

In development of a digital signage program, e.g., ad campaign or thelike, the DSS control processor 105 may guide a user through variousprocesses that are enhanced using knowledge acquired through thecognitive sciences. For example, information stored in the cognitivesciences database 130 may be applied to the choice of templates toproduce an optimal program layout and/or to the selection of content,such as whether content elements should be graphical, text, involvemovement, color, size, and/or to the implementation of other aspects ofprogram development. The DSS preferably includes the capability fordesigning alternative versions of a digital signage program toaccommodate diverse display types and viewing conditions in a mannerconsistent with the information stored in the cognitive sciencesdatabase 130.

FIG. 8 illustrates the process flow of creating and deploying contentusing the components and functionality of the DSS described above. Theprocess guides the user through a series of tools and scripts, andcreates 210 a number of alternative templates that specify howcategories of content elements might appear on the screen (e.g., thelocation, size, and orientation of elements such as text, graphics andvideos). The tools and scripts suggest recommended templates by drawingon three sets of information: a) principles from the cognitive andvision sciences regarding effective display of information, b) the goalsfor the content (e.g., way-finding, advertising), and c) the knownattributes of the digital signage network (e.g., size and shape of thedifferent displays, different viewing distances, and viewer demographicsacross the network).

For example, the tools and scripts might help a user determine whetheran element should be represented graphically or via text. The tools andscripts might also help a user determine which of a large number ofpre-defined templates are appropriate given the viewing conditionsacross the network, goals for the content, and if available, metricsregarding the types of templates that have been effective from previouscampaigns. The tools and scripts might further help a user determinewhether target and distractor elements of the content are properlypositioned, dimensioned or otherwise presented (e.g., proper color,intensity, etc.), and whether the desired order of targetattention/recognition by the viewer is achievable given the state of thecontent.

The process walks the user through a series of tools and scripts togenerate 220 the particular content elements that will later be placedwithin the templates created at block 210. The individual contentelements can include specific text messages, static images, animations,movie clips, sound bites, etc. Each element could have many variants,and software helps the user determine which elements of content can becombined within a template, the rules for how those elements can becombined, and the parameters on which the content elements can bemanipulated during the content creation process. For example, it may belegal to change the color or color intensity of a font duringdeployment, but not the color of the face of a famous person used in thetemplate.

The software tools and scripts may facilitate content generation bydrawing on multiple sets of information, including: a) data regardingthe types of content elements that were effective in previous campaigns,b) principles from the cognitive and vision sciences, and c) the knownattributes of the digital signage network. After the content is created,in this example, user interaction is no longer necessary.

Content creation is enhanced at block 230. The process may involvevarious constraints to combine elements and templates to create a numberof versions of content. The first time through this process, theconstraints may be based on: a) the factors previously used in creationof templates and content elements above, b) pre-programmed guidelinesfor how to combine elements and templates, and c) goals for the piece ofcontent being deployed. On subsequent passes through this block, theprocess may also use effectiveness data (e.g., sales or inventory data,data resulting from performing true or quasi-/correlationalexperimentation) to alter existing content/templates or create noveltemplates (through interpolation) and elements before creating newversions of content. Because each display in a network may havedifferent attributes (e.g., different lighting levels, noise levels,shape, size, and mean viewing distances), a unique version of contentmay be created for each display in the network. The content isdistributed 240 across the digital signage network, with adjustmentsmade thereto in view of the DSS/display attributes.

FIG. 9 is a flowchart illustrating an exemplary implementation of theDSS system in accordance with an embodiment of the invention. Theimplementation involves a sporting goods retailer with 200 stores. Theretailer desires to advertise four overstocked products and fourproducts that are not overstocked but that have higher profit marginsthan the overstocked products. The goal of the campaign is to maximizegross profit while eliminating excessive inventory of the overstockeditems. That is, once the excessive inventory is eliminated, the goalwill simply reduce to maintaining a balanced inventory at each storelocation.

Using cognitive/vision science driven software, the signage manager ofthe retailer creates 310 a number of different templates that will beused to develop content for each of the eight product lines. Thesetemplates include layout of messages, color schemes, and/or othervariables that make up the program. These templates can be used for eachof the eight product lines, and are not specific to a single product.Additionally, pre-existing or stock templates are available for useduring this phase.

After creating the base templates for this campaign, the signage managercreates 320 individual content elements that are needed to populate thetemplates. The individual elements are specific to the product linesbeing promoted, and include product branding and messages for givenproducts. As in the template creation process, creation of individualelements is guided by software wizards using cognitive/vision sciencedriven software.

The templates are automatically populated 330 with the individualcontent elements to generate a number of different content packages foreach of the eight products that the signage network is promoting.Potentially hundreds of differing versions of each content piece arecreated for each product line by merging elements with templates toaccommodate varying signage attributes such as screen size or viewingdistance.

Using pre-existing or learned knowledge about the signage network,content is distributed 340, such as by using algorithms that enablecollection of success metrics for individual pieces of content.According to some implementations, the content is distributed across thenetwork in a way that ensures proper counterbalancing, blocking, andconfound-free measurement can be made (e.g., in conformance withperforming a true experiment). Additionally, the deployment algorithmensures that relevant content is sent to the appropriate signs in thenetwork, considering network attributes, viewer demographics, andviewing conditions among others.

In some implementations, point of sale and sensor data is used whichallows the impact of the various content packages to be monitored andanalyzed to determine what templates and content elements, and theircombinations, are most effective for each screen on the network. Fromthis information, cause and effect, as well as return on investment canbe analyzed, enabling value-based billing. This example may determinewhether across all 200 stores, the signage system itself was responsiblefor X % increase in profits and Y % decrease in excessive inventory.Exploratory data analysis generates new possible network attributes. Forexample, there is a spike in sales when customers pick up product X andwhen content Y is concurrently shown. On the next iteration, this newnetwork attribute will be tested experimentally, not just measured froma correlation study. For example, the system may determine whethercontent pieces presented on X type screens is most effective usingY-type templates, and that the most effective content elements have XYZproperties.

Based on effectiveness data that may be acquired automatically (e.g.,via true experiments implemented by the signage network) or manually(e.g., sales information, inventory levels) 350, the system mayautomatically generate 360 new templates, new content elements, and newcombinations thereof. Again, using signage network attributes (both oldand new), the software deploys these new pieces of content across thenetwork. During the remainder of the campaign, the processes describedin blocks 330 through 360 may be repeated, for example, without userinteraction. The signage network manager is able to monitor the impactthat the content has on sales at any given point during the campaignwhile the system automatically attempts to achieve the campaign goals.

Upon completion of this campaign, templates and elements that weremanually or automatically generated during the campaign are availablefor future campaigns as well. Furthermore, the knowledge that was gainedregarding the types of templates and elements that are effective forparticular displays, demographics, or other factors, is used to createand distribute content more effectively across the network during futurecampaigns.

Determination of whether an experiment is a true experiment can beperformed proactively or retroactively with respect to running theexperiment. According to some embodiments, a computer may be used todetermine if an experiment that is yet to be performed is a trueexperiment. According to other embodiments, a computer may be used todetermine if an experiment that was previously performed is a trueexperiment. According to one approach, the computer determines, based oninformation provided by the user, whether an experimental designeliminates or controls confounds. In this example, the user entersinformation about the experiment, including the independent anddependent variables of the experiment.

The computer identifies situations that may produce confounds in theexperiment. The user selects the confound-producing situationsidentified by the computer that are present in the context of theexperiment. The computer prompts the user to identify steps taken toeliminate or control the identified confounds. The computer determinesif the combination of steps is sufficient to eliminate confounds in theexperiment. Details of performing a true experiment in the context ofthe present invention are further disclosed hereinbelow and in commonlyowned U.S. patent application Ser. No. 11/321/340, filed Dec. 29, 2005under Attorney Docket No. 61290US002, which is hereby incorporatedherein by reference.

FIG. 10 is a block diagram of a system for developing and/ordistributing content using cognitive/vision science driven software inaccordance with embodiments of the present invention. The system shownin FIG. 10 includes a computer 402 coupled to a display 404 and anetwork interface 406. The network interface 406 is coupled to a networkof displays 410, such as those of a DSS. The computer system 402 is alsocoupled to a cognitive sciences database 450.

The cognitive sciences database 450 includes several sets of rules ormodels each developed from principles of human cognitive and visionsciences. In this illustrative example, the rules and models, alsoreferred to herein as design rules or design models, include visualattention and perception rules 420, text readability rules 430, andmemory rules 440.

The visual attention and perception rules 420 may include rules ormodels that are based on how human perceptual systems process visualinformation. An illustrative example of a visual attention andperception model 420 is referred to as a saliency mapping model. Ingeneral terms, those portions of a given image which elicit a strong,rapid and automatic response from viewers, independent of the task theyare trying to solve, may be referred to as being visually salient. A redobject among green objects or horizontal lines among vertical linesrepresent two examples of such salient locations of an image.

The computer system 402 may be configured to provide for automaticdetection of salient parts of image information based on a saliencymapping model. Saliency may be computed in a number of ways as is knownin the art. Examples of such approaches which may be implemented in thecontext of the present invention are disclosed in U.S. PatentPublication No. 2006/0215922 and in U.S. Pat. No. 7,130,461, which areincorporated herein by reference hereinabove. Further details ofsaliency mapping models are described in Koch, C. and Ullman, S. “Shiftsin Selective Visual Attention: Towards the Underlying Neural Circuitry,”Human Neurobiology, 4:219-227, 1985; and two detailed computerimplementations: Itti, L., Koch, C. and Niebur, E., “A Model ofSaliency-Based Visual Attention for Rapid Scene Analysis,” IEEE Trans.Pattern Analysis & Machine Intell. (PAMI) 20:1254-1259, 1998 and Itti,L. and Koch, C. “A Saliency-Based Search Mechanism for Overt and CovertShifts of Visual Attention,” Vision Research 40:1489-1506, 2000, each ofwhich is hereby incorporated herein by reference.

According to one approach, the system shown in FIG. 10 may be configuredfor determining a saliency map, which may be a two-dimensional map thatencodes salient objects in a visual environment. The saliency map of agiven scene, for example, expresses the saliency of all locations inthis image. The saliency map is the result of competitive interactionsamong feature maps for image features including color, orientation,texture, motion, and depth, among others, that interact within andacross each map. At any time, the currently strongest location in thesaliency map corresponds to the most salient object. The value in themap represents the local saliency of any one location with respect toits neighborhood. By default, the system directs attention towards themost salient location. A second most salient location may be found byinhibiting the most salient location, causing the system toautomatically shift to the next most salient location.

By way of example, original content may be input to a saliency mappingmodel, such as in the form of a scanned or digitized image of theoriginal content. The computer system 402 may produce a saliency map ofthe content image, indicating the most salient locations of the imagepreferably in order. The output of the saliency mapping model mayindicate these salient locations using a box or other shape incombination with a number or letter, thus indicating the locations andorder of saliency of the image. These locations/order indicators can beused to provide a comparison between the content designer's intendedsaliency locations/ordering and the actual saliency locations/orderingas determined by the computer system 402.

The computer system 402 may generate recommendations to the designer vianarrative or imagery output that can improve saliency and/or achieve thedesired saliency/ordering of salient locations. The computer system 402may alternatively produce altered forms of the original contentautomatically in a manner that achieves the designers desired saliencymapping/ordering requirements. In this manner, the computer system 402may, without user intervention, analyze original content, develop asaliency map therefrom, determine if saliency requirements of the useror rule/model have been met, and, if not, generate one or more versionsof adjusted content that meets the saliency requirements of the user orrule/model.

Other visual attention/perception rules 420 may be defined for visualattention guiding attributes that can enhance the visual attention ofviewers to displayed content, effectively “guiding” the viewers toallocate attention to the display or portions of the display. Guidingattributes define aspects of individual content elements orrelationships between multiple content elements. Guiding attributes canbe used in a first mode, to attract the visual attention of viewers to adisplay, and be used in a second mode, during presentation of contentonce the viewer is present within the display space. For example, a rulemay be defined that regulates the number and spatial combination ofspecific strong guiding attributes that are present in the displayedcontent at any moment in time in order to maximize the attractiveness ofthe displayed content to the viewer, given the specific combination ofstrong attributes that exist in the visual environment in which thedisplay is located. Once the visual attention of the viewer has beenattracted and is within the display space, as indicated by a camera orproximity sensor, for example, the rule may allow for the combination ofboth strong and weak guiding attributes, or allow use of combinations ofstrong and weak attributes for guiding the viewer's visual attentionwithin the display content.

It is understood that there are two categories of guiding attributes,strong and weak guiding attributes. Strong guiding attributes include:size, color, orientation, motion, curved vs. straight, stereoscopicdepth, aspect ratio, monocular depth, and line termination. Weak guidingattributes include: novelty, intersection, color changes, semanticcategory, and faces.

A rule 420 may be defined that limits the number of strong guidingattributes present in the display of content at any given time. It isunderstood in the art that the presence of greater than a small numberof instances (e.g., four instances) of any one strong guiding attributein a content presentation at any given time weakens the “strength” ofthis strong guiding attribute with respect to guiding visual attention.The computer system 402 may be configured to track strong and,optionally, weak guiding attributes in a visual array of contentpresented on a display at any given time. If greater than 4 instances ofany one of the strong guiding attributes are detected at any given time,the computer system 402 may alert the designer or take automaticcorrective action by modifying the content to eliminate the duplicativestrong guiding attribute(s) in excess of 4 or other numeric threshold.

In another illustrative example, it is assumed that the content designerwishes to increase the likelihood that newly added content be seen bythe viewer. The computer system 402 may scan the content to determinethe identity and number of strong guiding attributes already used in thecontent, and recommend use of an unused (or least used) strong guidingattribute to draw attention to the newly added content element. Inanother illustrative example, the environment may be evaluated, such asby use of a camera or other sensors, to determine the type and number ofstrong guiding attributes present in the display environment. Based onthis environmental knowledge, the computer system 402 may recommendalteration (or automatically alter) of the content so that the combinednumber of strong guiding attributes present in the content at any onetime and in the display environment at the same time does not exceed the“maximum number of strong guiding attributes” threshold discussed above.This content may be adjusted dynamically by the computer system 402 inview of both content and display environmental visual attributes toincrease the effectiveness of content display.

Text readability may be defined in terms of one or more design rules ora model. For example, text readability may be defined in terms ofseveral parameters, including text size, reading speed (based on movingtext and/or speed of moving viewer, viewer dwelling time), font style,luminance, contrast, color, and viewing distance, among others.According to one approach, a minimum font or text size as a function oftext contrast may be defined as:

font size=7.434*exp(−contrast/0.6297)+5.028,

where font size is given in angular size (arc min.), and contrastrepresents text contrast defined as (L_(t)−L_(b))/L_(b), where L_(t) isthe text luminance and L_(b) is the background luminance. Additionaldetails of this model are described in Krebs, W. and Ahumada, Jr., A, “ASimple Tool for Predicting the Readability of a Monitor,” Proceedings ofthe Human Factors and Ergonomics Society 46^(th) Annual Meeting—2002,pp. 1659-1663, which is hereby incorporated herein by reference. Thecomputer system 402 may be configured to measure font size of contenttext and determine if the minimum font size of such text as definedabove is met. If not, the computer system 402 may indicate violation ofthis rule and/or alter the text in a manner that satisfies the font sizerule. Other text readability parameters may similarly be determined andadjusted by the computer system 402.

For example, as sensor or data from other sources regarding thedistances of viewers relative to a display is acquired, the system mayautomatically adjust the text size to improve readability according tothe distance information. Font size, which is measured in retinal arcminutes, may be adjusted systematically in relation to changes in viewerdistances from the display to maintain readability according to theequation above.

Memory rules or models 440 may also be implemented by the computersystem 402 to enhance viewer coding (e.g., visual, phonological, and/orsemantic coding), retention, and recall. Rules regarding working andlong-term memory may be defined and implemented by the computer system402. Memory rules 440 may be developed for meeting particular goals,such as the goal of viewers comprehending a comparison of informationand remembering desired information resulting from the comparison.

It is well understood that the duration of human working memory withoutrehearsal is about 2 seconds. In other words, absent rehearsal orrepetition, information in working memory can be lost in about 2seconds. It is assumed, in this illustrative example, that a contentdesigner wishes to design content such that a viewer encodes a firstpiece of information in working memory and also wishes that the viewerretain this first piece of information in working memory when a secondpiece of information is presented. In order to ensure that the firstpiece of information is not lost prior to presentation of the secondpiece of information, a memory rule 440 may ensure or recommend that thesecond piece of information be presented within 2 seconds ofpresentation of the first piece of information.

For example, the content designer may have the goal of presenting acomparison of a client bank's interest rate and that of a competitorbank. In order to ensure that the two interest rates are retained inworking memory for the comparison, the second of the two interest ratesis to be presented within 2 seconds of presentation of the firstinterest rate, per the working memory duration rule 440.

Principles of primacy and recency may also be defined in terms of memoryrules 440. For example, the computer system 402 may be configured toorder or re-order presentation of a sequence of information in a mannerthat increases the likelihood that the more important information inthis sequence is transferred to long-term memory. For example, asequence, series or pattern of information may be presented in anadvertisement for display. The information may be text or graphicobjects, such as numbers, letters, icons, pictures (e.g., of product onsale) or other information. Primacy and recency memory rules 440 may beapplied that order or re-order the informational objects so that themore important objects are preferentially positioned at the beginningand end of the sequence, with the less important (e.g., less profitable)informational objects being positioned in the middle portion of thesequence, series or pattern.

The principle of rehearsal may also be defined by one or more memoryrules 440. For example, a more important product of several products maybe shown more frequently than other less important products. In thisway, rehearsal or repetition of presentation of the more importantproducts in an advertisement increases the likelihood that the morefrequently presented products will be remembered by the viewer.

The principle of memory capacity may be defined in terms of one or morememory rules 440. It is understood in the art that the capacity ofworking memory is about four “chunks” of information. A “chunk” ofinformation represents anything that has a unitary representation inlong-term memory. Four chunks may be represented by four letters ornumbers that have little association. However, a multiplicity ofletters, numbers, objects, and the like that have a strong associationmay define a chunk. For example, the acronym NATO is formed frommultiple letters, but is defined as a chunk, as NATO has a unitaryrepresentation in long-term memory to most adults, for example.

A memory rule 440 may be defined that limits the number of chunks thatare presented at any given time in order to maximize the likelihood thatthe presented chunks are processed by the viewer and transferred tolong-term memory. For example, the computer system 402 may scan forchunks and notify the content designer if greater than four chunks havebeen presented at any given time.

These and other principles of cognitive and vision sciences may bedefined in terms of rules or models, including those described inGoldstein, E. Bruce, “Cognitive Psychology, Connecting Mind, Research,and Everyday Experience,” Thompson/Wadsworth 2005, which is herebyincorporated herein by reference.

As was discussed previously, the complexity of the cognitive sciencesdatabase may vary from relatively simple to very complex. It isunderstood that the rules and models shown in FIG. 10 are forillustrative purposes only, and that a cognitive sciences database ofthe present invention may incorporate one or more aspects of one or moreof these rules and models. These and other rules and models may bedeveloped that associate a particular cognitive/vision science principleor set of principles to a content development rule or model that can beimplemented by a computer to detect or ensure adherence to suchrule/model.

Those skilled in the art will appreciate that cognitive/vision scienceprinciples other than, or in addition to, those described herein may beincorporated into a cognitive sciences database for use in contentdevelopment and distribution in accordance with the present invention.

FIG. 11 is a flowchart illustrating various processes associated withcontent development and modification using one or more cognitive/visionsciences models in accordance with the present invention. FIG. 11 isdirected to methods that provide for computer-assisted analysis ofcontent by one or more cognitive and vision sciences (CVS) models.Content is provided or developed 502 by a content designer. The contentis input 504 to a computer system that implements one or more CVSmodels, such as a computational model of visual attention, a textreadability model or a model of human memory. The CVS model or modelsperform an analysis 506 on the content and produce 512 an output basedon the analysis results. Information representative of environmentalconditions at the presentation locations and/or goals for the contentmay be inputs 508, 510 to the model(s). For example, the type andconfiguration of displays, average distances between displays andviewers, average speeds or dwelling times as between viewers anddisplays may be environmental condition information 508 that is input tothe model(s).

Goal information 510 that may be input to the model(s) may include goalsthat are associated with each of the various models, such as acomputational model of visual attention, a text readability model or amodel of human memory. Typical goal information may include saliencymapping goals, such as specific elements of the content to be perceivedby viewers and the desired order in which such specific elements are tobe perceived. Other goal information 510 may include improving oroptimizing text readability based on text size and/or scrolling textrate relative to viewer location and/or speed at which viewers pass by agiven display. Additional goal information 510 may include maximizingmemory coding, retention, and/or recall of content by viewers, such asby conforming to memory capacity and duration rules of a given model.

In some implementations, the output represents recommendations forchanging 516 the content in conformance with a given model's rules orgoals. The recommendations may take several forms, such as a narrativeform or images. For example, a menu of possible attributes of thecontent that may be changed 514 can be presented to the user. The menuof attributes may include a range of attribute values that may bechanged by the user, yet still conform with a given model's rules orgoals.

In other implementations, the output represents a modified form of theoriginal content produced automatically 518 by the computer implementedCVS model or models. A number of variations of modified content may beautomatically produced, each of which satisfies the rules or goals ofthe model or models. The user may then select a desired version of themodified content 514 for presentation 520. Alternatively, the computermay select one or more of the versions for presentation. In otherimplementations, the various versions of modified content may be subjectto a designed experimental process that improves or optimizes contentpresentation effectiveness for a number of networked displays,preferably on a display-by-display basis, as is discussed in greaterdetail with reference to FIG. 12 below.

FIG. 12 is a flowchart illustrating various processes associated withcontent development and modification of same using one or morecognitive/vision sciences models and results from true experimentationpreferably implemented by a digital signage system in accordance withthe present invention. According to the embodiment shown in FIG. 12,content may be developed and distributed 602 in conformance withcognitive and vision sciences rules or models, such as in mannersdiscussed hereinabove. A true experiment may be performed 604 to improveor optimize presentation effectiveness of the content. Conducting thetrue experiment may include identifying 606 dependent variables, such asa goal of increasing sales of a particular product. Independentvariables may be identified 608, such as parameters associated with oneor more CVS models (e.g., text readability, visual attention and/ormemory parameters). Content may be modified 610 in view of the resultsfrom the true experiment. For example, content may be modified 612 on adisplay-by-display basis, based on improved or optimized parameters foreach display. The modified content may be presented 614 on each of thedisplays in a manner optimized for each display.

Additional true experimentation may be conducted to further improve oroptimize content presentation, particularly under changing environmentalconditions or a change in the goals or intended message of the content.It is understood that quasi-experiments and correlational experimentsmay be performed in addition to, or to the exclusion of, a trueexperiment. Details of suitable quasi-/correlational experimentalmethods that may be adapted in accordance with the present invention aredisclosed in U.S. Patent Publication No. 2005/039206, which is herebyincorporated herein by reference.

According to various embodiments, an expert system may be configured toimplement a true experiment in the context of the present invention. Theexpert system may include a design processor having various hardwarecomponents including a central processing unit (CPU) and memory, amongother components. The memory stores computer instructions that controlthe processes for designing the experiment and stores informationacquired from the user that are needed for the experimental design.Under control of the software, the CPU algorithmically selects orgenerates questions to elicit information from a user. The questions arepresented to the user via an output device of a user interface that iscoupled to the design processor. For example, the user interfacetypically includes a display device, such as a liquid crystal display(LCD) or other type of display device for presenting the questions tothe user. The user interface also includes one or more input devices,such as a touch screen responsive to a finger or stylus touch, a mouse,keyboard, voice recognition, or other type of input device. The userenters responses to the questions via one or more input devices(s) ofthe user interface. The design processor can determine the appropriatedescriptive and inferential statistics for the experiment based on theexperimental design and the characteristics of the independent anddependent variables.

The design processor may be configured to identify the informationrequired to design a true experiment and selects or generates a seriesof questions that elicit responses from the user providing the requiredinformation. The questions are presented to the user via a userinterface. User responses to the questions are received via the userinterface and are transferred to the design processor. The designprocessor extracts information from the user responses and designs atrue experiment based on the information. The expert system has thecapability to collect information at specific steps that is relevant toother steps. For example, knowledge that the dependent variable iscontinuous in step X means a particular type of statistical analysisshould be used in step Y. The system uses data from previous steps tocomplete later steps. For example, if the data has already beenacquired, the system would not ask the user for the same informationagain. The user would not need to know that the information was relevantto both steps. If the data were not available from previous steps, thesystem would ask the user for the needed data.

A true experiment includes development of a hypothesis or objective.Dependent and independent variables are identified, and at least twolevels of one or more independent variable are used. A control group andtreatment groups are formed and samples are randomly assigned to levelsof the independent variable. There is some kind of method forcontrolling for or eliminating confounding variables. For example, in adigital signage experiment, the system would guide the user through theprocess of controlling for carry over effects by 1) balancing andcounterbalancing the order with which pieces of content are shown atlocations across the network; and or 2) ensuring that two pieces ofexperimental content are not shown within a block of time in whichviewers could see both pieces of content while in the store; and or 3)ensuring that sufficient time has elapsed before data are collectedbetween when the content switches from one version of experimentalcontent and another version of experimental content such that at least95% of possible viewers who were in the store at the time of the contentchange would have left the store. If all of these elements areappropriately applied, the experiment produces results that can be usedto make statistical inferences about the relationship between thedependent and independent variables. The expert system described hereinallows a user who is unsophisticated in the complexities of trueexperimental design to design an experiment that produces substantiallyconfound-free results and can be used to determine and quantify anycausal relationship between independent and dependent variables.

Embodiments of the invention are directed to an expert system that hasthe capability of designing a true experiment based on user input. Aspreviously mentioned, the use of the expert system relieves the user ofhaving any foundation in the theory or practice of experimental design.A true experiment has at least two levels of an independent variable.The expert system elicits information from a user required to chooseindependent and dependent variables for the experiment. For example, ina digital signage experiment, the expert system might ask the userquestions such as: “If content X (where X is any piece of content inwhich the user wants to experimentally evaluate) is effective, what arethe changes in the world that you would expect to happen as a result ofshowing content X? The system would provide a number of possible changessuch as: sales of a particular product will increase; foot traffic in aparticular location in the store will increase; consumers will inquirewith staff regarding the features of a particular product; consumerswill pick a particular product off the shelf; and other, where other isany other change that is not included in the system's stored set ofpossible changes.

Those skilled in the art will appreciate that each of these possible“changes in the world” correspond to a possible dependent variable thatcould be measured in an experiment designed to test the effectiveness ofcontent X. Likewise, the expert system could guide the user through theprocess of picking control content analogues to a placebo in a drugstudy. For example, the expert system would ask the user to identifycontent that would not be related in any way to the goal of content X.With respect to threats to internal validity, the expert system, via thesequence of questions and user responses, identifies threats to internalvalidity, and may initiate processes for controlling these threats, suchas through balancing, counterbalancing and/or blocking, and/orrandomization.

The expert system, based on user input, is capable of implementingprocesses for assigning samples randomly to groups so that each samplein an experiment is equally likely to be assigned to levels of theindependent variable. The expert system is also capable of designing anexperiment that includes randomization, counterbalancing and/orblocking. The system may assist the user in selecting independentvariables or levels of independent variables, and assists the user inselecting dependent variables based on factors associated with internaland/or external validity of the experiment. For example, the systemcould obtain the necessary information to conduct power analyses onvarious combinations of independent and dependent variables, provide theuser with the results of the various power analyses, the domain specificterms, and values that the user understands (“Using sales data tomeasure the effectiveness of this piece of content would take 8 weeksand cost $1400 whereas using sensor data would take 2 weeks and cost$800”).

In some configurations, in addition to designing the true experiment,the expert system may aid the user in performing one or more ofconducting true experiments, collecting data, statistically analyzingthe data, and interpreting the results of the experiments. In additionto the experiment design processor and user interface previouslydescribed, the expert system may also include an experiment controlprocessor configured to automatically or semi-automatically control theexecution of the experiment. An experiment analysis processor may alsobe included that is configured to analyze the experimental data and/orinterpret the results of the experiment. The functions of the controlprocessor and the analysis processor are enhanced through knowledge ofhow the experiment was designed by the design processor.

For example, because the analysis processor will have receivedinformation regarding the independent and independent variables (e.g.,whether the independent variables (IVs) and dependent variables (DVs)are continuous or discrete), the analysis processor would have much ofthe necessary information to choose the appropriate statistical test toapply to the data from the experiment. For example, if there is one IVwith two discrete levels and one continuous DV, then a T-Test may beselected by the analysis processor for the inferential statistical testwhereas if there is one IV with two discrete levels and one DV with twodiscrete levels, then a Chi-Squared test may be used for the inferentialstatistical test. Likewise, because the analysis processor will haveaccess to information from the design processor regarding whichexperimental conditions are diagnostic of particular hypotheses, theanalysis processor would have most or all of the information needed todetermine which experimental and control conditions should bestatistically compared and reported to the user. Additional detailsregarding methods and systems for designing and implementing trueexperiments in the context of the present invention are disclosed incommonly owned U.S. patent application Ser. No. 11/321/340, filed Dec.29, 2005 under Attorney Docket No. 61290US002, which is incorporated byreference hereinabove.

Application of cognitive and vision sciences, alone or in combinationwith designing and implementing true experiments in accordance with thepresent invention, allows users with little or no background in thecognitive and vision sciences (or designing true experiments) to applythese disciplines in order to create more effective content. Thisfunctionality can be used in either a single or multi-screenenvironment. On a system-wide level, application of cognitive and visionsciences provides input and constraints for the automated content designsystem in order to tailor content on a screen-by screen basis. Forexample, if the average viewing distance is known for each network sign,then the component for applying the cognitive and vision sciences willdetermine the ideal font size for each display, and this informationwill be used by the automated content design component to generate textwith those font-size parameters.

Automated content design and development according to the presentinvention may also provide for the automatic generation of new templatesand application of transformations to existing elements. New templatesand elements may be generated to improve the content effectiveness.Content development tools of the present invention may also be used togenerate unique versions of pieces of content for each player in thesystem.

In some implementations, users may be prompted to provide input or mayuse information supplied from other components regarding the networkattributes and factors that underlie content effectiveness. Knowledgefrom the cognitive and visions sciences may be used to extrapolate, fillin, and otherwise explore the information space for the particularpieces of content the system aims to enhance. The functionality of thecontent development tools provides the ability to generate completelynew content that is not simply a reconfiguration of deployed templatesor elements associated with deployed versions of content.

The foregoing description of the various embodiments of the inventionhas been presented for the purposes of illustration and description. Itis not intended to be exhaustive or to limit the invention to theprecise form disclosed. Many modifications and variations are possiblein light of the above teaching. For example, embodiments of the presentinvention may be implemented in a wide variety of applications. It isintended that the scope of the invention be limited not by this detaileddescription, but rather by the claims appended hereto.

1. A computer-assisted method, comprising: developing content forpresentation on a display, the content comprising content elements;providing display information about the display and display environment;facilitating, by way of computer assistance, the development of thecontent using the display information and a database comprising designrules or models based on principles of cognitive and vision sciences. 2.The method of claim 1, wherein facilitating the development of thecontent comprises generating user perceivable recommendations fordeveloping the content, the recommendations consistent with design rulesor models.
 3. The method of claim 1, comprising alerting a user inresponse to violation of one or more of the design rules or models. 4.The method of claim 1, wherein facilitating the development of thecontent comprises automatically adjusting the content in response tonon-compliance with the design rules or models.
 5. The method of claim1, wherein facilitating the development of the content comprisesfacilitating layout of the content elements in compliance with thedesign rules or models.
 6. The method of claim 1, wherein facilitatingthe development of the content comprises facilitating selection of thecontent elements in compliance with the design rules or models.
 7. Themethod of claim 1, wherein facilitating the development of the contentcomprises facilitating selection of one or more attributes of thecontent elements in compliance with the design rules or models.
 8. Themethod of claim 7, wherein the one or more attributes of the contentelements comprise one or more of color, brightness, size, orientation,font, movement, presentation duration or flash rate, display location,and number of content elements concurrently presented on the display. 9.The method of claim 1, wherein facilitating the development of thecontent comprises facilitating selection of content element attributesbased on one or more attributes of the display or display environment.10. The method of claim 9, wherein the one or more attributes compriseone or more of display type, display size, display shape, averageviewing distance from the display, average speed of viewer movementrelative to the display, viewer dwelling time, ambient lighting at alocation of the display, and time of day of content presentation on thedisplay.
 11. The method of claim 1, comprising receiving user input datacomprising information regarding each content element, the informationcomprising one or both of content goal and intended message, whereinfacilitating the development of the content comprises facilitatingdevelopment of the content using the design rules or models and the userinput data.
 12. The method of claim 1, wherein the content elementscomprise graphics, text, video clips, still images, audio clips or webpages.
 13. The method of claim 1, wherein facilitating the developmentof the content comprises facilitating development of the content for aplurality of networked displays, the method further comprisingfacilitating selection of content element attributes based on one ormore attributes of each of the displays.
 14. The method of claim 1,wherein facilitating the development of the content comprisesfacilitating development of the content for a plurality of networkeddisplays, the method further comprising: receiving user input datacomprising information regarding each content element, the informationcomprising one or both of content goal and intended message;facilitating user identification of attributes of the networked displaysor display environments that have implications for content development;and facilitating the development of the content using the design rulesor models, user input data, and display attributes.
 15. The method ofclaim 1, further comprising facilitating, by way of computer assistance,modification of the developed content in compliance with the designrules or models.
 16. The method of claim 15, wherein the developedcontent is modified in response to a change in one or more attributes ofthe displays or display environments.
 17. The method of claim 16,wherein the one or more attributes comprise one or more of display type,display size, display shape, average viewing distance from the display,average speed of viewer movement relative to the display, viewerdwelling time, ambient lighting at a location of the display, and timeof day of content presentation on the display.
 18. The method of claim1, wherein facilitating the development of the content comprisesfacilitating development of the content for a plurality of networkeddisplays, the method further comprising modifying, by way of computerassistance, the developed content for particular displays of theplurality of networked displays in response to a change in an attributeof the particular displays or environments associated with theparticular displays.
 19. The method of claim 1, wherein the databasecomprises design rules or models based on one or more of user visualattention, human memory, and text readability.
 20. The method of claim1, comprising performing a true experiment that produces results usefulfor improving or optimizing effectiveness of content presentation.
 21. Asystem, comprising: a database comprising design rules or models basedon principles of cognitive and vision sciences; a user interfacecomprising a display; and a processor coupled to the database and userinterface, the processor configured to facilitate development of contentfor presentation on the display using the design rules or models andinformation about the display or display environment, the contentcomprising content elements.
 22. The system of claim 21, wherein theprocessor is configured to generate user perceivable recommendations fordeveloping the content, the recommendations consistent with design rulesor models.
 23. The system of claim 21, wherein the processor isconfigured to generate an alert for a user in response to violation ofone or more of the design rules or models.
 24. The system of claim 21,wherein the processor is configured to automatically adjust the contentin response to non-compliance with the design rules or models.
 25. Thesystem of claim 21, wherein the processor is configured to facilitatelayout of the content elements in compliance with the design rules ormodels.
 26. The system of claim 21, wherein the processor is configuredto facilitate selection of the content elements in compliance with thedesign rules or models.
 27. The system of claim 21, wherein theprocessor is configured to facilitate selection of one or moreattributes of the content elements in compliance with the design rulesor models.
 28. The system of claim 27, wherein the one or moreattributes of the content elements comprise one or more of color,brightness, size, orientation, font, movement, presentation duration orflash rate, display location, and number of content elementsconcurrently presented on the display.
 29. The system of claim 21,wherein the processor is configured to facilitate selection of contentelement attributes based on one or more attributes of the display ordisplay environment.
 30. The system of claim 29, wherein the one or moreattributes comprise one or more of display type, display size, displayshape, average viewing distance from the display, average speed ofviewer movement relative to the display, viewer dwelling time, ambientlighting at a location of the display, and time of day of contentpresentation on the display.
 31. The system of claim 21, wherein theprocessor is configured to receive user input data comprisinginformation regarding each content element, the information comprisingone or both of content goal and intended message, the processor furtherconfigured to facilitate development of the content using the designrules or models and the user input data.
 32. The system of claim 21,wherein the content elements comprise graphics, text, video clips, stillimages, audio clips or web pages.
 33. The system of claim 21, whereinthe processor is configured to facilitate development of the content fora plurality of networked displays, the processor further configured tofacilitate selection of content element attributes based on one or moreattributes of each of the displays.
 34. The system of claim 21, whereinthe processor is configured facilitate development of the content for aplurality of networked displays, the processor further configured to:receive user input data comprising information regarding each contentelement, the information comprising one or both of content goal andintended message; facilitate user identification of attributes of thenetworked displays or display environments that have implications forcontent development; and facilitate the development of the content usingthe design rules or models, user input data, and display attributes. 35.The system of claim 21, wherein the processor is configured tofacilitate modification of the developed content in compliance with thedesign rules or models.
 36. The system of claim 35, wherein theprocessor is configured to modify the developed content in response to achange in one or more attributes of the displays or displayenvironments.
 37. The system of claim 36, wherein the one or moreattributes comprise one or more of display type, display size, displayshape, average viewing distance from the display, average speed ofviewer movement relative to the display, viewer dwelling time, ambientlighting at a location of the display, and time of day of contentpresentation on the display.
 38. The system of claim 21, wherein theprocessor is configured to facilitate development of the content for aplurality of networked displays, the processor further configured tofacilitate modification of the developed content for particular displaysof the plurality of networked displays in response to a change in anattribute of the particular displays or environments associated with theparticular displays.
 39. The system of claim 21, wherein the databasecomprises design rules or models based on one or more of user visualattention, human memory, and text readability.
 40. The system of claim21, wherein the processor is configured to perform a true experimentthat produces results useful for improving or optimizing effectivenessof content presentation.
 41. The system of claim 21, comprising one ormore sensors for sensing one or more attributes of the displayenvironment.
 42. The system of claim 41, wherein the one or more sensorscomprise a video camera.
 43. The system of claim 41, wherein the one ormore sensors comprise one or more proximity sensors.